Effective AI implementation relies not only on the quantity of data but also on technical expertise. Let's explore the significance of having a skilled data team for AI projects, learn about the Small Data movement and examine how far we can go with no-code or low-code AI platforms.
Explore how Netflix Maestro and Apache Airflow, two powerful workflow orchestration tools, can complement each other. Delve into their features, strengths, and use cases to uncover whether they are companions or competitors.
Explore the potential of Large Language Models (LLMs) changing the future of mental healthcare and learn about how to apply Parameter-Efficient Fine-Tuning (PEFT) to create an AI-powered mental health support chatbot by example
Explore the essence of pragmatic Data Engineering through a task-solving journey and learn why you should ask WHY?
Discover the basics of using Gemini with Python via VertexAI, creating a Web UI with NiceGUI and using Jinja2 to construct modular prompts
Discover the basics of using Gemini with Python via VertexAI, creating APIs with FastAPI, data validation with Pydantic and the fundamentals of Retrieval-Augmented Generation (RAG)
Discover the basics of extensibility with BigQuery User-Defined Functions (UDFs) with a little Easter egg hunt game
Learn how to use Apache Flink with this demo that uses Stanford CoreNLP to analyze the Twitch chat in real-time
Practical examples how to use DuckDB as a tool for data wrangling based on Pokémon API data
Practical example on how to create an Airflow DAG to fetch data from the StarCraft II API, utilize DuckDB for processing and Streamlit for visualizing
Make the most out of your BigQuery usage, burn data rather than money to create real value with some practical techniques
This article explains the Apache Airflow basics and guides you through the process setting up a local environment as well as writing your first DAG using the TaskFlow API
Time for a new project...
